CBDA_Stopping_Criteria {CBDA}R Documentation

Stopping Criteria function for Compressive Big Data Analytics

Description

This CBDA function generates a stopping criteria for the *max_covs - min_covs* nested predictive models generated in the previous step. It also populates the CBDA object.

Usage

CBDA_Stopping_Criteria(label = "CBDA_package_test", Kcol_min = 5,
  Kcol_max = 15, Nrow_min = 30, Nrow_max = 50, misValperc = 0,
  M = 3000, workspace_directory = tempdir(), max_covs = 100,
  min_covs = 5, lambda = 1.005)

Arguments

label

This is the label appended to RData workspaces generated within the CBDA calls

Kcol_min

Lower bound for the percentage of features-columns sampling (used for the Feature Sampling Range - FSR)

Kcol_max

Upper bound for the percentage of features-columns sampling (used for the Feature Sampling Range - FSR)

Nrow_min

Lower bound for the percentage of cases-rows sampling (used for the Case Sampling Range - CSR)

Nrow_max

Upper bound for the percentage of cases-rows sampling (used for the Case Sampling Range - CSR)

misValperc

Percentage of missing values to introduce in BigData (used just for testing, to mimic real cases).

M

Number of the BigData subsets on which perform Knockoff Filtering and SuperLearner feature mining

workspace_directory

Directory where the results and workspaces are saved

max_covs

Top features to include in the Validation Step where nested models are tested

min_covs

Minimum number of top features to include in the initial model for the Validation Step

lambda

Fisher test threshold for MSE (=1.005 by default)

Value

value


[Package CBDA version 1.0.0 Index]